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In�uence of Interleukin-18 and Interleukin-17Receptor A gene polymorphisms on the risk ofthyroid cancer among Chinese Han populationYanhai Yin 

Hainan General HospitalFen Li 

Hainan General HospitalLiangqian Tong 

Haikou people's hospitalChaoqun Wang 

Hainan General HospitalKun Liang 

Hainan General HospitalChunru Chen 

Hainan General HospitalRuqi Dai 

Hainan General HospitalBo Yuan  ( boyuan201901@163.com )

Hainan General Hospital

Research article

Keywords: Thyroid cancer, Interleukin, IL-18, IL-17RA, polymorphisms

Posted Date: December 2nd, 2019

DOI: https://doi.org/10.21203/rs.2.17911/v1

License: This work is licensed under a Creative Commons Attribution 4.0 International License.  Read Full License

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AbstractBackground Thyroid cancer (TC) is a common endocrine pathology with an increasing incidenceworldwide. It has been reported that high genetic impact is involved in the pathogenesis of TC, as well ascytokines, especially the interleukins play a crucial role in it. This study was designed to detect theassociation of IL-18 and IL-17RA polymorphisms with TC risk.

Methods This case-control study conducted 365 TC patients and 503 healthy controls from Chinese Hanpopulation. Three selected SNPs (IL-18 rs360718, IL-18 rs1946519, and IL-17RA rs4819554) weregenotyped to investigate the possible association of the polymorphisms with the risk of TC. Multifactordimensionality reduction (MDR) was used to analyze the interactions of SNP-SNP.

Results IL-17RA rs4819554 was associated with the decreased risk of TC under dominant model (OR =0.76, 95% CI = 0.56-0.99, p = 0.04). IL-18 rs360718 signi�cantly decreased the risk at age ≤ 44 years (Cvs. A, OR = 0.63, 95% CI = 0.41-00.97, p = 0.033; CC vs. AA, OR = 0.12, 95% CI = 0.01-0.91, p = 0.040). Onthe contrast, among people older than 44 years, IL-18 rs1946519 (C vs. A, OR = 1.77, 95% CI = 1.03-3.06, p= 0.040) shown an increased risk with TC. MDR analysis revealed a positive interaction between theSNPs.

Conclusion The present study �rstly demonstrated that IL-18 rs360718, rs1946519 and IL-17RArs4819554 polymorphisms might be related to thyroid cancer. The results were signi�cantly worthy offurther validation by larger studies.

1 IntroductionThyroid cancer (TC), a common endocrine malignancy, accounting for more than 90% of endocrinecancers, had constantly increased worldwide recent years[1]. TC led the �fth most common cancer inwomen in the United States[2], while the estimates of cancer incident cases and deaths were 143.9thousand and 6500 respectively in China[3]. Although the exact pathophysiologic mechanisms of TCremained elusive, accumulating evidence indicated that the inter-individual genetic factors, especially thesingle nucleotide polymorphisms (SNPs) in tumor-associated genes took essential part in the geneticsusceptibility to TC[4-7].

Cytokines were molecules that contribute to regulate activation, growth, and differentiation of sometarget cells[8]. Importantly, they were pro-and anti-in�ammatory mediators that played a crucial role in theinduction and effector phases of the in�ammatory and immune responses, and functioned as a regulatorin development and growth of both normal and neoplastic thyroid cells[9]. Interleukin-18 (IL-18), apleiotropic pro-in�ammatory cytokine that induced interferon-gamma (IFN-γ) production and wasinvolved in T helper type 1 development, was cloned for the �rst time in 1995[10]. Previous studies andclinical trials were indicated not only the antitumoral activity of IL-18 but also the possibility and e�cacyof using it for therapeutic purposes. Additionally, evaluating the relevance between SNPs of IL-18 anddifferent neoplastic conditions had attracted much attention[11]. Besides, interleukin-17 receptor A (IL-

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17RA) was identi�ed as the receptor of IL-17A and IL-17F[12]. It was expressed on a wide range of tissuesand cell types, including several types of cancer cells[13]. Therefore, IL-17RA had become a point ofinterest for its mediation of some important signaling pathway.

Although, polymorphisms of IL-18 and IL-17RA obtained much attention with the risk of TC, there werenone of relevant research in Han Chinese population. The present study was aim to detect the possibleassociation among the polymorphisms of three SNPs (IL-18 rs360718, IL-18 rs194651, and IL-17RArs4819554) in Han Chinese population. This might reveal a new perspective of the prevention andtreatment of thyroid cancer in the future.

2 Methods2.1 Ethical approval of the current hospital-based study

The current case-control study was obtained the permission by the Review Board of the Hainan GeneralHospital. All subjects provided written inform consent to be included in the study.

2.2 Study participants

A total of 365 TC patients (mean age: 43.98 ± 15.17) and 503 healthy control subjects (mean age: 44.16± 12.37) were enrolled in this case-control study. All patients were Chinese Han adults and recruited fromthe Hainan General Hospital. The inclusion criteria for the patients were: patients who were recentlydiagnosed and identi�ed as TC, according to diagnostic imaging and histopathological examination. Thehealthy controls without medical history of any type of cancer were randomly recruited from the healthcheckup at the same time.

2.3 SNPs selection and genotyping

We identi�ed two single nucleotide polymorphisms (SNPs) in IL-18 and one in IL-17RA with a minor allelefrequency (MAF) > 0.05 in Chinese Han population from the NCBI dbSNP database(http://www.ncbi.nlm.nih.gov/projects/SNP) and the 1000 Genomes Projects(http://www.internationalgenome.org/). The 5mL blood samples from all participants were collected invacutainers which contained Ethylenediaminetetraacetic acid (EDTA). To extract gDNA, the GoldMagwhole blood genomic DNA puri�cation kit (GoldMag Co. Ltd., Xi’an, China) was used and then, theextracted gDNA was stored at -80℃ until analysis. The MassARRAY iPLEX platform (Agena, San Diego,CA, U.S.A) was used for evaluating IL-18 and IL-17RA gene polymorphisms. The primers for ampli�cationand single base extension were designed using the Agena Bioscience Assay Design Suite V2.0 software.Subsequently, Data management was conducted by Agena Bioscience 4.0 software.[14]. Genotyping wascompleted by two laboratory technicians in a double-blinded method. Importantly, we randomly selectedabout 10% of the samples to repeat genotyping for the quality control, the reproducibility was > 99%.

2.4 Bioinformatics analysis

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Online softwares, HaploReg v4.1 (https ://pubs.broad institute.org/mamma ls/haplo reg/haplo reg.php)and SNP info Web Server (https ://snpin fo.niehs .nih.gov/snpin fo/index.html), took essential part inpredicting the possible functional effects on these candidate SNPs. GEPIA datasets (http://gepia .cancer-pku.cn/) was used to predict the expression of IL-18 and IL-17RA.

2.5 Data analysis

SPSS 20.0 (SPSS Inc., IBM, USA) statistical software and PLINK software were used for this study. Thecategorical variables were evaluated using Pearson’s.χ2 test, and student’s t-test was performed toanalyze the differences in the age distribution between the cases and controls. Hardy-Weinbergequilibrium (HWE) was tested by χ2 test for each SNP which was selected in this study. χ2 test or Fisher’sexact test were used to compare the genotype and allele frequencies between cases and controls. Forrespective genotype, we used logistic regression analysis to assess the relevance of selected SNPs withTC risk by odds ratios (ORs) and 95% con�dence intervals (CIs) based on previous methods[15].Haploview software (version 4.2) and PLINK software were used for analyzing the Linkage disequilibrium(LD) and haplotype[16]. Multifactor dimensionality reduction (MDR) (version 3.0.2) was performed toevaluate the interactions between SNP and SNP in the TC risk[17].A two-tailed p-value <0.05 wasstatistically signi�cant for all the analyses.

 

3 Results3.1 Characteristic of the study participants

IL-17RA and IL-18 polymorphisms were analyzed in 365 patients (97 men and 268 women) and 503unrelated disease controls (137 men and 366 women). The characteristic of participants included in thisstudy were listed in Table 1. The cases and controls appeared to be adequately matched on age and sexas suggested by the student-t and χ2 tests respectively (p = 0.857, p = 0.877).

3.2 Genotyping of the SNPs in IL-18 and IL-17RA

SNPs in IL-18 ( rs360718 and rs1946519) and IL-17RA (rs4819554) were successfully genotyped. Thedetails of these SNPs and potential function predicted by HaploReg database about them were presentedin Table 2. The Hardy-Weinberg equilibrium (HWE) tests for the IL-18 and IL-17RA polymorphisms wereshown in Table 2, and the results indicated that the frequencies of genetic polymorphisms were all in theHWE (p value > 0.05). Additionally, mRNA levels of IL-18 was up-regulated in TC (p < 0.01, Fig 1), whilethere was no statistically signi�cant in mRNA level of IL-17RA gene based on GEPIA database(supplementary �gure 1). And then, the association between the expression of IL-18 and the prognosis ofTC which predicted by GEPIA database was shown in supplementary �gure 2. It indicated that theexpression of IL-18 had a modest relationship with the prognosis of TC (hazard ratio = 0.32, Log-rank p =0.04).

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To evaluate the associations between IL-18, IL-17RA variants and the TC risk, �ve inheritance models(Allele, Genotype, Dominant, Recessive and Log-additive) adjusted for potential confounding variables(age, and gender) were applied. The results shown in Table3 indicated that IL-17RA rs4819554polymorphism was associated with the decreased risk of thyroid cancer under dominant model (GG-GAvs. AA, OR = 0.76, 95% CI = 0.56-0.99, p = 0.040). However, IL-18 rs360718 and rs1946519polymorphisms presented no statistically difference in genotype frequencies between the TC patients andthe healthy controls (p ≥ 0.05). Logistic regression analyses indicated that none of these two SNPs in IL-18 were associated with any change of susceptibility to TC (Table 3).

Strati�cation analysis by age and gender was performed. The results of subgroup test of age indicatedthat IL-18 rs360718 (C vs. A, OR = 0.63, 95%CI = 0.41-0.97, p = 0.033; CC vs. AA, OR = 0.12, 95% CI = 0.01-0.91, p = 0.040) showed a decreasing-risk effect at age ≤ 44 years (Table 4). On the contrast, amongpeople older than 44 years, IL-17RA rs4819554 (G vs A, OR = 0.76, 95%CI = 0.58-1.00, p = 0.047) wasassociated with the modestly decreased risk of TC which need to be further investigated (Table 4). IL-18rs1946519 (C vs. A, OR = 1.77, 95% CI = 1.03-3.06, p = 0.040) shown an increased risk. Also, the results ofstrati�cation analysis by gender were listed in Table 4. There was no statistically signi�cant differencebetween man and woman.

Furthermore, we researched the linkage disequilibrium (LD) and haplotype analyses of the SNPs in IL-18.The reconstructed LD plot was presented in Figure 2, and the LD block was comprised of two SNPsincluding IL-18 rs360718 and IL-18 rs1946519. The frequencies distribution of haplotypes in the casesand controls were showed in Table 5. The results indicated an association of CA haplotype with amodestly increased risk of TC which needed to be further detected in the future (OR = 1.34,95% CI = 1.00-1.78, p = 0.047).

3.4 SNP-SNP interactions.

SNP-SNP interactions were analyzed by MDR method. Obviously, there were interactions between locusand locus presented in a dendrogram and the Fruchterman-Reingold in Figure 3. Subsequently, analysisfor 3 SNPs in IL-17RA and IL-18 were presented in Table 6. The results indicated that IL-17RA rs4819554was the best single-locus model to predict TC (testing accuracy = 0.526, CVC = 9/10, p = 0.626). The besttwo-locus model was the combined of IL-18 rs1946519 and IL-17RA rs4819554 (testing accuracy = 0.514,CVC = 8/10, p = 0.008). The three-locus model included IL-17RA rs4819554, IL-18 rs1946519 and IL-18rs360718 (testing accuracy = 0.527, CVC = 10/10, p = 0.001).

4 DiscussionThis case-control study aimed to investigated the potential effects of IL-18 and IL-17RA genepolymorphisms on TC in Chinese Han population. Our �ndings suggested that IL-17RA rs4819554 wasassociated with the decreased risk of TC. Especially in patients who were older than 44 years old, amodestly statistical relevance between IL-17RA rs4819554 and decreasing risk effect of TC deservedfurther research. Additionally, IL-18 rs360718 was detected to shown a signi�cantly decreased risk with

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TC in patients under 44 years of age, whereas rs1946519 had an effect of increased risk with TC inpatients 44 years and older. To our knowledge, this is the �rst study to report the effect of these SNPs inTC individuals.

IL-18 gene was located on chromosome 11 in humans and functionally, IL-18 was �rst identi�ed as “IFNγ-including factor” isolated in the serum of mice [18], [19]. In the previous studies, the expression of IL-18were signi�cantly associated with multiple kinds of tumors, such as breast cancer, hepatocellularcarcinoma, renal-cell carcinoma, and lung cancer.[19]. It also has been reported that IL-18 polymorphisms(rs1946519, rs360718) were associated with TC risk in Iran and Korean population [11, 23], however, therewas none of reports about these correlations with Chinese Han population. At present,  we �rstlyexamined the role of IL-18 genetic polymorphisms (rs360718 and rs1946519) and the susceptibility to TCin Han Chinese population, and found that IL-18 SNP rs1946519 conferred increased risk to TC in thepatients older than 44 years, while IL-18 rs360718 shown a signi�cantly decreasing-risk effect with TC inpatients under 44 years of age. Haplotype analysis revealed that the CA haplotype in IL-18 rs360718 wasmodestly corelated with an increased risk of TC which needed to be further detected. Therefore, it washighly speculated that IL-18 rs1946519 and rs360718 polymorphisms may affect the progression ofthyroid cancer related to the age of patients. Further large-scale studies are needed to verify the results ofour �ndings.

IL-17 family, included six polypeptides, IL-17A-F, and �ve receptors, IL-17RA-E[24]. The chemokine IL-17, aproin�ammatory cytokine, was mainly produced by T-helper cells (Th17), macrophages and CD8+ T cells.Importantly, the function of IL-17 was mediated by IL-17RA, also named CD217, which was located in22q11.1 and had been recognized as a valuable biomarker for diverse diseases[25, 26]. Upon thestimulation with IL-17, IL-17RA initiated the activation of downstream signaling pathways to induce theproduction of pro-in�ammatory molecules[13, 27]. Further evaluation revealed that IL-17RA couldfunction as an inhibitor of signaling through the way called receptor-mediated internalization of theligand[12, 28]. Several research had indicated the IL-17 played important role in the development andprevention of TC[29, 30]. Moreover, it had reported that IL-17 and IL-17RA polymorphisms were correlationwith TC risk in Korean population[31]. In the present study, we �rstly found that IL-17RA (rs4819554)polymorphism was associated with the decreased risk of thyroid cancer under dominant model (GG-GAvs AA, OR = 0.76 95% CI = 0.56-0.99, p = 0.04). Furthermore, among people older than 44 years, IL-17RArs4819554 was associated with the modestly decreased risk (G vs A, OR = 0.76, 95% CI = 0.58-1.00, p =0.047) of TC. These decreasing-risk effects deserve further discussion by in-depth functional and largesample size studies to elucidate the impact of IL-17RA rs4819554 polymorphism on TC. Finally, thepotential SNP-SNP interactions among IL-18 rs1946519, rs360718 and IL-17RA rs4819554 weredetermined by MDR. The analysis of the SNP-SNP interactions presented strong interaction betweenthese SNPs regarding susceptibility to TC.

With the exceptions of the �ndings about the interaction between IL-18, IL-17RA polymorphism and TCrisk, several limitations of this study should be pointed out. Firstly, we only genotyped three SNPs in theIL-18 and IL-17RA in this study. More other SNPs should be examined in future studies. Second, our study

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enrolled only a moderate number of subjects, and we needed to conducted a larger survey to con�rm ourstudy.

5 ConclusionsIn conclusion, our �ndings indicated relevance between IL-18, IL-17RA and thyroid cancer in Han Chinesepopulation. The large population-based prospective and further functional studies are being planned toprovide evidences which were more accurate about the in�uence of genetic polymorphisms on TC.

DeclarationsFunding

This research received no external funding.

Con�ict of Interest

The authors have no actual or potential con�icts of interest related to this manuscript.

Author contributions

Bo Yuan, Yanhai Yin, Fen Li: Conceptualization. Yanhai Yin and Fen Li: Methodology. Liangqian Tong andChaoqun Wang: Software. Kun Liang, Chunru Chen and Rufen Dai: Validation. Yanhai Yin, Fen Li andLiangqian Tong: Data curation. Yanhai Yin: Writing-original draft preparation. Yanhai Yin and Fen Li:Writing-review and editing. Yanhai Yin and Fen Li: Visualization

Acknowledgements

We thank all authors for their contributions and support. We are also grateful to all participants forproviding blood samples.

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TablesCharacteristics Cases   Controls p  n=365   n=503  Age (years) mean ± SD 43.98±15.17     44.16±12.37 0.852Age (years)        ≤ 44 172 (47.1%)   239 (47.5%)  > 44 193 (52.9%)   264 (52.5%)  Gender        Male 97 (26.6%)   137 (27.2%) 0.877Female 268 (73.4%)   366 (72.8%)  

           

Table 1 Characteristics of patients with thyroid cancer and controls

 

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Table 2 The information and HWE about the SNPs

SNP ID Genes Chr:Position

Role Alleles(A/B) MAF p-valuefor

HWE

Haploreg SNPinfoweb

serverCases Controls

rs360718 IL-18 11:112164016

5’UTR C/A 0.118 0.146 0.150 Promoterhistonemarks,

Enhancerhistonemarks,DNAse,Proteinsbound,GRASP

QTL hits,SelectedeQTL hits

TFBS

rs1946519 IL-18 11:112164784

Upstream C/A 0.527 0.481 0.653 Promoterhistonemarks,

Enhancerhistonemarks,DNAse,Motifs

changed,SelectedeQTL hits

TFBS

rs4819554 IL-17RA

22:17084145 Upstream G/A 0.375 0.421 0.854 Promoterhistonemarks,

Enhancerhistonemarks,DNAse,Motifs

changed,Selected

eQTLhits,

TFBS

SNP, single nucleotide polymorphism;

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MAF, minor allele frequency;

eQTL, expression quantitative trait loci;

TFBS, transcription factor binding sites

 

 

Table 3 Relationships between the IL-18, IL-17RA SNPs and thyroid cancer risk

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SNP ID Model Genotype Case Control 

Adjusted by age and gender

  OR (95% CI) p

IL-18 rs360718 

Allele A 640 857 1.00  

C 86 147 1.20 (0.99-1.46) 0.098

Genotype AA 281 370 1.00  

CC 4 15 0.35 (0.11-1.06) 0.064

CA 78 117 0.87 (0.63-1.22) 0.439

Dominant AA 281 370 1.00  

CC-CA 82 132 0.82 (0.60-1.12) 0.214

Recessive CA-AA 359 487 1.00  

CC 4 15 0.36 (0.12-1.09) 0.071

Log-additive - - - 0.79 (0.60-1.05) 0.099

IL-18rs1946519 

Allele A 336 514 1.00  

C 374 476 1.20 (0.99-1.46) 0.063

Genotype AA 78 136 1.00  

CC 97 117 1.44 (0.98-2.13) 0.063

CA 180 242 1.30 (0.92-1.18) 0.133

Dominant AA 78 136 1.00  

CC-CA 277 359 1.34 (0.98-1.85) 0.070

Recessive CA-AA 258 378 1.00  

CC 97 117 1.21 (0.89-1.66) 0.225

Log-additive - - - 1.20 (0.99-1.46) 0.064

IL-17RA rs4819554 

Allele A 456 579 1.00  

G 274 421 0.83 (0.68-1.01) 0.057

Genotype AA 146 166 1.00  

GG 55 87 0.72 (0.48-1.08) 0.109

GA 164 247 0.76 (0.56-1.02) 0.064

Dominant AA 146 166 1.00  

GG-GA 219 334 0.76 (0.56-0.99) 0.040

Recessive GA-AA 310 413 1.00  

GG 55 87 0.84 (0.58-1.22) 0.360

Log-additive - - - 0.83 (0.68-1.01) 0.057

 

SNP, single nucleotide polymorphism; OR, odds ratio; 95% CI, 95% confidence interval.

p values were calculated by logistic regression analysis with adjustments for age and gender.

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p < 0.05 means the data is statistically significant.

 

 

 

 

Table 4 Relationships between the candidate SNPs and thyroid cancer risk according to the stratification by ageand gender

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SNP ID Allele/genotype Control Case OR (95%CI)

p Control Case OR(95%CI)

p

Age   > 44       ≤ 44      

IL-18rs360718

A 454 334 1.00   75 36 1.00  

  C 72 50 0.94 (0.64-1.39)

0.770 403 306 0.63(0.41-0.97)

0.033

  AA 195 145 1.00   175 136 1.00  

  CC 4 3 1.01 (0.22-4.58)

0.995 11 1 0.12(0.01-0.91)

0.040

  CA 64 44 0.94 (0.60-1.46)

0.768 53 34 0.84(0.51-1.37)

0.477

IL-18rs1946519

A 269 172 1.00   229 168 1.00  

  C 247 206 1.30 (1.00-1.70)

0.050 245 164 1.10(0.83-1.45)

0.522

  AA 70 38 1.00   58 42 1.00  

  CC 59 55 1.77 (1.03-3.06)

0.040 113 84 1.21(0.69-2.12)

0.514

  CA 129 96 1.37 (0.85-2.21)

0.200 66 40 1.22(0.75-1.98)

0.431

IL-17RArs4819554

A 297 244 1.00   282 212 1.00  

  G 227 142 0.76 (0.58-1.00)

0.047 194 132 0.91(0.68-1.20)

0.905

  AA 83 79 1.00   83 67 1.00  

  GG 48 28 10.63 (0.36-1.10)

0.103 39 27 0.83(0.46-1.50)

0.529

  GA 131 86 0.70 (0.46-1.05)

0.086 116 78 0.84(0.54-1.29)

0.420

Gender   Male       Female      

IL-18rs360718

A 234 169 1.00   623 471 1.00  

  C 40 23 0.80 (0.46-1.38)

0.416 107 63 0.78(0.56-1.09)

0.141

  AA 101 73 1.00   269 208 1.00  

  CC 4 0 - - 11 4 0.47 0.202

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(0.15-1.50)

  CA 32 23 0.99 (0.54-1.84)

0.982 85 55 0.84(0.57-1.23)

0.364

IL-18rs1946519

A 144 88 1.00   348 248 1.00  

  C 128 96 1.23 (0.84-1.79)

0.284 107 278 1.19(0.95-1.49)

0.127

  AA 39 20 1.00   97 58 1.00  

  CC 31 24 1.52 (0.71-3.24)

0.282 86 73 1.42(0.91-2.23)

0.123

  CA 66 48 1.43 (0.74-2.77)

0.285 176 132 1.25(0.84-1.87)

0.263

IL-17RArs4819554

A 152 123 1.00   427 333 1.00  

  G 118 71 0.74 (0.51-1.09)

0.124 303 203 0.86(0.68-1.08)

0.192

  AA 44 39 1.00   122 107 1.00  

  GG 27 13 0.54 (0.25-1.20)

0.131 60 42 0.80(0.50-1.28)

0.347

  GA 64 45 0.79 (0.45-1.41)

0.433 183 119 0.74(0.52-1.05)

0.091

SNP, single nucleotide polymorphism; OR, odds ratio; 95% CI, 95% confidence interval.

p values were calculated by logistic regression analysis with adjustments for age.

p < 0.05 indicates statistical significance.

 

Table 5 Haplotype frequencies in IL-18 rs360718 and their association with thyroid cancer

Haplotype Frequency Crude analysis Adjusted by age and gender

Case Control OR (95% CI) p OR (95% CI) pAC 0.53 0.48 1.21 (1.00-1.47) 0.050 1.21 (1.00-1.47) 0.051CA 0.89 0.85 1.34 (1.00-1.78) 0.048 1.34 (1.00-1.78) 0.048

AA 0.36 0.37 0.94 (0.77-1.15) 0.541 0.94 (0.77-1.15) 0.548

OR, odds ratio; 95% CI, 95% confidence interval.

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p values were calculated using Pearson’s χ2 tests with and without adjustment by gender and age.

p < 0.05 indicates statistical significance.

 

 

Table 6 MDR analysis of SNP-SNP interactions in relation to TC risk.

Model TrainingBal. Acc

TestingBal. Acc

OR (95%CI)

Testing χ2

value

pvalue

CVC

rs4819554 (IL-17RA) 0.535 0.526 1.34(1.00,1.80)

0.238 0.626 9/10

rs1946519(IL-18), rs4819554 (IL-17RA) 0.549 0.514 1.48(1.11,1.98)

7.008 *0.008 8/10

rs1946519 (IL-18), rs360718 (IL-18),rs4819554 (IL-17RA)

0.559 0.527 1.64(1.22,2.21)

10.762 *0.001 10/10

MDR, multifactor dimensionality reduction;

Bal. Acc., balanced accuracy;

CVC, cross-validation consistency;

OR, odds ratio; 95% CI, 95% confidence interval.

p values were calculated using χ2 tests. *p < 0.05 indicates statistical significance.

 

Figures

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Figure 1

IL-18 gene expression is up-regulated in TC compared with that in normal thyroid tissues. Each barrepresents the average level of IL-18 expression. Error bars represent the standard deviation of the meanvalue. Data was extracted from the GEPIA database (http://gepia.cancer-pku.cn/). Asterisk indicatesstatistical signi�cance (p < 0.01).

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Figure 2

Haplotype block map for two SNPs in IL-18 gene.

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Figure 3

SNP-SNP interaction dendrogram (A) and Fruchterman-Reingold (B). The dendrogram and Fruchterman-Reingold comprises a spectrum of colors that represent a continuum from synergy to redundancy, orangerepresents a relatively high degree of synergy (positive information gain) and blue represents redundancy(negative information gain).

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